MétaCan
Menu
Back to cohort
Record W2135499567 · doi:10.1177/1557988312464038

The Limitations of Language

2012· article· en· W2135499567 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAmerican Journal of Men s Health · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsMcGill University
FundersCanadian Institutes of Health Research
KeywordsPhotovoiceVariety (cybernetics)Photo elicitationExpression (computer science)StorytellingQualitative researchPsychologyEmotional expressionApplied psychologyDevelopmental psychologyComputer scienceSociologyLinguisticsSocial scienceNarrativeVisual arts

Abstract

fetched live from OpenAlex

The semistructured, open-ended interview has become the gold standard for qualitative health research. Despite its strengths, the long interview is not well suited for studying topics that participants find difficult to discuss, or for working with those who have limited verbal communication skills. A lack of emotional expression among male research participants has repeatedly been described as a significant and pervasive challenge by health researchers in a variety of different fields. This article explores several prominent theories for men's emotional inexpression and relates them to qualitative health research. The authors argue that investigators studying emotionally sensitive topics with men should look beyond the long interview to methods that incorporate other modes of emotional expression. This article concludes with a discussion of several such photo-based methods, namely, Photovoice, Photo Elicitation, and Visual Storytelling.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.829
Threshold uncertainty score0.427

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.654
GPT teacher head0.682
Teacher spread0.027 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it